I have a question about the Dynare function computing endogenous priors for likelihood estimation. I understand that it is based on the Christiano-Trabandt-Walentin paper and that it targets variances.
I would be interested in targeting also the first-order autocovariances. I get how to modify the « empirical » part of the code computing data moments. However, I’m not sure how to modify the part computing the theoretical moments. It seems to me that additional inputs to the endogenous_priors function would be needed to do that, but I can’t tell their exact names in the Dynare syntax. Any help from the devs would be welcome.
Also, at the end of the code, there is a commented line corresponding to Del Negro - Schorfheide type VAR priors. It shows the expression of the likelihood, but doesn’t explain how to compute the various elements. I was curious if someone ever wrote a Dynare code to implement this form of endogenous priors.